Klimentidis, Y. C., Going, S. B., Chen, Z., Lohman, T. G., & Bea, J. W. (2014). High genetic-risk individuals benefit less from resistance exercise intervention. International Journal of Obesity.
Klimentidis, Y. C., Arora, A., Chougule, A., Zhou, J., & Raichlen, D. A. (2015). FTO association and interaction with time spent sitting. International journal of obesity (2005).
Multiple studies have revealed an interaction between a variant in the FTO gene and self-reported physical activity on body mass index (BMI). Physical inactivity, such as time spent sitting (TSS) has recently gained attention as an important risk factor for obesity and related diseases. It is possible that FTO interacts with TSS to affect BMI, and/or that FTO's putative effect on BMI is mediated through TSS.
Duarte, C. W., Klimentidis, Y. C., Harris, J. J., Cardel, M., & Fernández, J. R. (2015). Discovery of phenotypic networks from genotypic association studies with application to obesity. International journal of data mining and bioinformatics, 12(2), 129-43.
Genome-wide Association Studies (GWAS) have resulted in many discovered risk variants for several obesity-related traits. However, before clinical relevance of these discoveries can be achieved, molecular or physiological mechanisms of these risk variants needs to be discovered. One strategy is to perform data mining of phenotypically-rich data sources such as those present in dbGAP (database of Genotypes and Phenotypes) for hypothesis generation. Here we propose a technique that combines the power of existing Bayesian Network (BN) learning algorithms with the statistical rigour of Structural Equation Modelling (SEM) to produce an overall phenotypic network discovery system with optimal properties. We illustrate our method using the analysis of a candidate SNP data set from the AMERICO sample, a multi-ethnic cross-sectional cohort of roughly 300 children with detailed obesity-related phenotypes. We demonstrate our approach by showing genetic mechanisms for three obesity-related SNPs.
Klimentidis, Y. C., & Arora, A. (2015). Interaction of Insulin Resistance and Related Genetic Variants with Triglyceride-Associated Genetic Variants. Circulation: Cardiovascular Genetics.
Klimentidis, Y. C., Lemas, D. J., Wiener, H. H., O'Brien, D. M., Havel, P. J., Stanhope, K. L., Hopkins, S. E., Tiwari, H. K., & Boyer, B. B. (2013). CDKAL1 and HHEX are associated with type-2 diabetes-related traits among Yup'ik people. Journal of diabetes.
Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with type-2 diabetes (T2D), mainly among individuals of European ancestry. We examined the frequency of these SNPs and their association with T2D-related traits in an Alaska Native study population with a historically low prevalence of T2D. We also investigated whether dietary characteristics that may protect against T2D, such as n-3 polyunsaturated fatty acid (n-3 PUFA) intake, modify these associations.
